What are the questions that are being asked?
Evidence gathered by this project from HEI/FEIs indicates a preference for two basic kinds of questions when seeking to generate effective business intelligence:
- Subject based enquiries: such as accurate student numbers, potential markets, research performance or benchmarking, the answers to which feed into the planning process
- Know-how based enquiries: such as 'what do we as an organisation have to do in order to ensure that we have the right processes in place to gather, present and use information and data effectively?'
Subject based questions
As is clear from the survey results, interest is most predominantly expressed regarding the area of finance and costing. Return on investment and justification of expenditure are key concerns particularly during an economic downturn.
Some are asking
'What are our salary commitments for the next financial year?'
'What is the full economic cost of teaching every programme we offer?'
Others ask
'How much income does each academic generate?'
'Is my department in profit and financially sustainable?'
'Which are our most profitable courses, financially and academically?'
There is interest in the relationship between students and finance too:
'I would like to do more future modelling of student numbers to show impact on finances, and to be able to model the cost of programmes too'.
There is also concern about maintaining student quotas and the risk of funding body penalties should institutions over-recruit.
There is widespread awareness of the need to maximise student information and data in order to compete successfully against peer institutions and gain full understanding of the student lifecycle, pathways and experience . Areas of concern may relate to helping applicants to make informed choices about which university and programme to study, or to improving the student experience and identifying those at risk, (thus focusing on student well-being). Others include apparently basic but in reality rather complex questions such as 'How many students have we actually got?' and 'how can I track non-completions more accurately?'and the more complex 'How can I undertake proper analysis of a specific student cohort?'.
Staff data and teaching performance data are in many areas integrally associated with student data, and are equally essential to sound planning and management. Here issues frequently appear to relate to accurate and real time measurement of staff/student ratios, the calculation of academic workloads, the accurate reporting of staff contact hours and the question of
'Which staff of which type teach which students on which modules'.
Others concentrate on the staff themselves, such as
'How is our staffing profile changing?'
'What attracts, motivates and retains staff at the university?'
'What are our staff costs?'
'What is the size and nature of expected staffing cuts?'
Equally key to strategic planning and competitive edge is knowledge of staff and institutional research performance. Information requiring statistical answers may relate to such issues as the success rate of research proposals submitted, or overall research income generated or who is the most successful principal investigator in a particular area. For example 'What metrics should we use to measure research grants, contracts and awards, research income, research student numbers and admissions reporting?' Qualitative responses are needed for such questions as 'What is the quality of our research activity, where are our strengths and weaknesses? Can we measure these in relation to RAE/REF?'
Measurement of performance both across the institution and by benchmarking against other institutions is a requirement in all institutions but complex in execution. Areas of interest range from the straightforward 'How are we performing against our targets?' to those requiring more complex knowledge about performance trends relating to student numbers across various faculties and departments. Typical issues concern which courses are the most successful in terms of achievement, retention, employability and satisfaction. Key performance indicators (KPIs) are high on the agenda: for example 'How do we develop appropriate KPIs at department, faculty and institutional levels particularly in emerging areas such as internationalisation and enterprise?' Also difficult to compute is 'How do we measure the links between qualifications on entry, learning and teaching practice and outcomes in order to measure added value in a meaningful way?' Others seek a greater ability to develop performance metrics that cross functional areas of data (staff, space, student, finance) - for example the financial contribution per metre square of space allocated to an academic department. And data management issues arise too: 'I would like to be able to integrate the student dataset in order to be able to produce performance management/management information data, as well as use the data for operational purposes.'
Benchmarking is one of the most vexed issues for many institutions. In order to retain a competitive edge it is crucial to be able to gauge performance against that of peer institutions. It seems that many are able to source fairly high level data but are unable to access data at a more granular - and therefore meaningful - level. Some ask
'How do I get benchmarking data across HEIs on per capita expenditure on corporate and academic services that I can rely on as reliable and consistent - and is at a more detailed level than currently available?'
'How do we benchmark against other institutions and make informative comparisons?' Another states 'I am frequently asked about comparable data from other institutions/subjects and that is incredibly difficult, if not impossible to obtain.' And a data management angle again: 'I want to know how (or if) other institutions are able to present "dashboard style" KPI information which is benchmarked against other HEIs or benchmark groups'
Benchmarking is acknowledged as one of the main challenges faced by institutions in relation to BI and is currently the subject of a HEFCE-funded HESA initiative.
Tied in with benchmarking to some extent is marketing. It is difficult to take a market position when you do not know how others are performing. Institutions want to be able to establish what the market trends are in terms of student demand in each of the subject areas offered at undergraduate, postgraduate and international level, with some including knowledge transfer and CPD. Others are seeking an increased toolset to look at student recruitment markets - current and potential - to inform marketing activity.
'What is our market position?'
'Most of our burning questions are about aggregate market demand and market share'
'What are our potential markets for new, or existing programmes of study? How do we compare with other HEIs?'
Strategic planning as an area of interest is often tied in with any of the other subject areas described above. Those who have highlighted it in its own right may ask general questions such as where to concentrate strategic planning and change management effort in order to improve performance and cost effectiveness. It seems that more would like to be able to use data to inform future strategic planning relating to staff redundancies, budget parameters and the like, or to forecast business plans, combining HR data, financial data, research awards and overheads and spend patterns, by business unit.
In relation to the BI focus of our survey, business and community engagement currently appears to be a topic of fairly limited interest and concern, but this is likely to change as institutions are increasingly required to explore additional sources of revenue. Issues in these areas range from how to use a Customer Relationship Management (CRM) system to manage colleagues' relationships with their external contacts better, to how to encourage academics to want to engage with local business and the community to empower them to flourish.
Surprisingly few respondents expressed a concern with obtaining information about estates management and the most efficient use of the institution's estate. Some want to know whether the university has sufficient, flexible teaching space capacity to meet the challenges of the next five years. Others ask 'How can we use the university's estate more effectively?'
Know-how based questions
Our record and information management resources provide further advice and guidance on how to improve the way in which information is managed within institutions.
Articulating the questions to which you want an answer is just the first stage however, and institutions are conscious that getting the answer can in itself be a complex process. Many acknowledge that their issues and areas of concern are also about underlying data and information management systems, and that ultimately business intelligence processes need to be in place in order to deliver solutions.
Therefore successful answers to many of the questions outlined in the sections above require robust data and information management practices. Those who focus their attention here acknowledge that successful business intelligence depends on good quality data, user friendly systems, the ability to draw data from disparate systems, to use data strategically, and to get buy in and ownership from staff across campus. Our 'What is BI?' section contains a 'checklist of required and desirable attributes' from any BI system.
From our research it is clear that many institutions have already embarked on BI projects, developing, for example, data warehouses, dashboards and web reporting tools. Further information on the range and nature of BI activity in the sector and how it can currently be profiled is available in this section of the infoKit.
There is clear appreciation that access to a single source of management information would help institutions to meet their planning challenges. This was expressed by one respondent as
'How we can share the same piece of data across different systems so that we streamline the data collection, input and access to core corporate planning data'.
It is clearly understood that this might embrace, for example, the planning model; student records system; timetabling; HR system; Transparent Approach to Costing (TRAC); the finance system; academic workload planning and so on. People also acknowledged that data is not always as accurate as it might be, as is evident in the following statements:
'We create lots of information, but not always the right data'
'Why can't we easily produce information drawing on reasonable to good quality data held in different systems?'
The need to produce user-friendly, accessible reports is also an issue:
'the biggest challenge is to use the information to produce visually powerful reports and succinct interpretation and explanation that allows senior management to rapidly reach a well informed decision'.
